Deep learning applications

• • Self-Driving Cars
  In self-driven cars, it is able to capture the images around it by processing a huge amount of data, and then it will decide which actions should be incorporated to take a left or right or should it stop. So, accordingly, it will decide what actions it should take, which will further reduce the accidents that happen every year.
• • Voice Controlled Assistance
  When we talk about voice control assistance, then Siri is the one thing that comes into our mind. So, you can tell Siri whatever you want it to do it for you, and it will search it for you and display it for you.
• • Automatic Image Caption Generation
  In self-driven cars, it is able to capture the images around it by processing a Whatever image that you upload, the algorithm will work in such a way that it will generate caption accordingly. If you say blue colored eye, it will display a blue-colored eye with a caption at the bottom of the image.
• • Automatic Machine Translation
  With the help of automatic machine translation, we are able to convert one language into another with the help of deep learning.

Limitations

• • It only learns through the observations.
• • It comprises of biases issues.

Advantages

• • It lessens the need for feature engineering.
• • It eradicates all those costs that are needless.
• • It easily identifies difficult defects.
• • It results in the best-in-class performance on problems.

Disadvantages

• • It requires an ample amount of data.
• • It is quite expensive to train.
• • It does not have strong theoretical groundwork.